Collective Motion, Sensor Networks, and Ocean Sampling

This paper addresses the design of mobile sensor networks for optimal data collection. The development is strongly motivated by the application to adaptive ocean sampling for an autonomous ocean observing and prediction system. A performance metric, used to derive optimal paths for the network of mo...

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Bibliographic Details
Published in:Proceedings of the IEEE 2007-01, Vol.95 (1), p.48-74
Main Authors: Leonard, Naomi Ehrich, Paley, Derek A., Lekien, Francois, Sepulchre, Rodolphe, Fratantoni, David M., Davis, Russ E.
Format: Article
Language:English
Subjects:
Adaptive sampling
autonomous underwater vehicles
Biosensors
cooperative control
coordinated dynamics
Cost function
Electrical & electronics engineering
Engineering, computing & technology
Ingénierie électrique & électronique
Ingénierie, informatique & technologie
Laws
Mathematical models
Mobile robots
mobile sensor networks
Networks
ocean sampling
Oceans
Optimization
Remotely operated vehicles
Sampling
Sampling methods
Sea measurements
Sensor arrays
Sensors
Steady flow
Temperature measurement
underwater gliders
Vehicle dynamics
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Summary:This paper addresses the design of mobile sensor networks for optimal data collection. The development is strongly motivated by the application to adaptive ocean sampling for an autonomous ocean observing and prediction system. A performance metric, used to derive optimal paths for the network of mobile sensors, defines the optimal data set as one which minimizes error in a model estimate of the sampled field. Feedback control laws are presented that stably coordinate sensors on structured tracks that have been optimized over a minimal set of parameters. Optimal, closed-loop solutions are computed in a number of low-dimensional cases to illustrate the methodology. Robustness of the performance to the influence of a steady flow field on relatively slow-moving mobile sensors is also explored
ISSN:0018-9219
1558-2256
1558-2256
DOI:10.1109/JPROC.2006.887295